A significant challenge in structural optimization of vehicle architectures for crash is handling
of the typically large number of quantities defining the input and system parameters. The use of
advanced composites materials increases this challenge by introducing more parameters and
complex failure behavior. This paper introduces a novel design workflow that can help reduce
the problem complexity for composite vehicle structures and provide for a more e
cient design
workflow. First a computationally e
cient prognosis method is introduced to smooth the design
space and reduce the number of required samples. Second a sensitivity analysis using the
Sobol decomposition is introduced to provide a parameter importance hierarchy. Results show
a reduction of 71.12% of required samples at the same time achieving a better quality design
space. The sensitivity analysis results in a reduction of 22 to 8 parameters.
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